Gemini 3.5 Flash Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.

google/gemini-3.5-flash-lite:batch 1.04858M context $0.15/M input $1.25/M output

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azure/us/gpt-5.6-sol 1.05M context $5.5/M input $33/M output

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azure/us/gpt-5.6-terra 1.05M context $2.75/M input $16.5/M output

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azure/us/gpt-5.6-luna 1.05M context $1.1/M input $6.6/M output

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azure/eu/gpt-5.6 1.05M context $5.5/M input $33/M output

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azure/eu/gpt-5.6-sol 1.05M context $5.5/M input $33/M output

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azure/eu/gpt-5.6-terra 1.05M context $2.75/M input $16.5/M output

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azure/eu/gpt-5.6-luna 1.05M context $1.1/M input $6.6/M output

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azure/gpt-5.5 1.05M context $5/M input $30/M output

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azure/us/gpt-5.5 1.05M context $5.5/M input $33/M output

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azure/eu/gpt-5.5 1.05M context $5.5/M input $33/M output

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azure/gpt-5.5-2026-04-23 1.05M context $5/M input $30/M output

Nex-N2.5 is an agentic model built to turn goals into working, verified outcomes. Its core strength is agentic coding within a visual feedback loop: it can explore codebases, implement multi-file...

nex-agi/nex-n2.5-mini:free 262.144K context Free input Free output

No provider description is available for this model yet.

azure/us/gpt-5.5-2026-04-23 1.05M context $5.5/M input $33/M output

GPT-6 Astra Pro is the same underlying model as [GPT-6 Astra](https://openrouter.ai/openai/gpt-6-astra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

openai/gpt-6-astra-pro:batch 1.05M context $5/M input $25/M output

No provider description is available for this model yet.

azure/eu/gpt-5.5-2026-04-23 1.05M context $5.5/M input $33/M output

Mercury 2.5 is the fastest reasoning LLM, and the latest diffusion LLM (dLLM) from Inception. Instead of generating tokens sequentially, Mercury 2.5 produces and refines multiple tokens in parallel, achieving...

inception/mercury-2.5-preview 260K context $0.2/M input $0.75/M output

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azure/gpt-5.4-mini 272K context $0.75/M input $4.5/M output

No provider description is available for this model yet.

azure/gpt-5.4-mini-2026-03-17 272K context $0.75/M input $4.5/M output

Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design...

qwen/qwen3.5-9b:batch 262.144K context $0.17/M input $0.25/M output

Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation...

google/gemini-3.1-pro-preview:batch 1.04858M context $1/M input $6/M output

No provider description is available for this model yet.

azure/gpt-5.4-nano 272K context $0.2/M input $1.25/M output

DeepSeek V4 Pro 0813 is a large-scale mixture-of-experts model from DeepSeek. This is the GA release of DeepSeek V4 Pro.

deepseek/deepseek-v4-pro-0813:batch 1.04858M context $0.66/M input $1.98/M output

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azure/gpt-5.4-nano-2026-03-17 272K context $0.2/M input $1.25/M output

Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text,...

qwen/qwen3.8-max-0902 1M context $2/M input $6/M output

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azure/o1 200K context $15/M input $60/M output

No provider description is available for this model yet.

azure/o1-2024-12-17 200K context $15/M input $60/M output

GPT-6 Astra Pro is the same underlying model as [GPT-6 Astra](https://openrouter.ai/openai/gpt-6-astra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

openai/gpt-6-astra-pro 1.05M context $10/M input $50/M output

Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be...

qwen/qwen3.8-27b 262.144K context $0.214/M input $2.55/M output

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azure/o3 200K context $2/M input $8/M output

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azure/o3-2025-04-16 200K context $2/M input $8/M output

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azure/o3-mini 200K context $1.1/M input $4.4/M output

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azure/o3-mini-2025-01-31 200K context $1.1/M input $4.4/M output

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azure/o4-mini 200K context $1.1/M input $4.4/M output

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azure/o4-mini-2025-04-16 200K context $1.1/M input $4.4/M output

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azure/us/gpt-4.1-2025-04-14 1.04758M context $2.2/M input $8.8/M output

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azure/us/gpt-4.1-mini-2025-04-14 1.04758M context $0.44/M input $1.76/M output

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azure/us/gpt-4.1-nano-2025-04-14 1.04758M context $0.11/M input $0.44/M output

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azure/us/gpt-5-2025-08-07 272K context $1.375/M input $11/M output

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azure/us/gpt-5-mini-2025-08-07 272K context $0.275/M input $2.2/M output

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azure/us/gpt-5-nano-2025-08-07 272K context $0.055/M input $0.44/M output

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azure/us/gpt-5.1 272K context $1.38/M input $11/M output

No provider description is available for this model yet.

azure/us/o1-2024-12-17 200K context $16.5/M input $66/M output

Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more efficient member of...

thinkingmachines/inkling-small:free 1.04858M context Free input Free output

Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more efficient member of...

thinkingmachines/inkling-small:batch 524.288K context $0.5/M input $1.2/M output

No provider description is available for this model yet.

azure/us/o3-2025-04-16 200K context $2.2/M input $8.8/M output

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azure/us/o3-mini-2025-01-31 200K context $1.21/M input $4.84/M output

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azure/us/o4-mini-2025-04-16 200K context $1.21/M input $4.84/M output